NgsRelate: Difference between revisions
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= Run example using | = Run example using only ngs data= | ||
Assume we have file containing paths to 100 BAM/CRAM files, then we can use ANGSD to estimate frequencies calculate genotype likelihoods while doing SNP calling and dumping the input files needed for the NgsRelate program | Assume we have file containing paths to 100 BAM/CRAM files, then we can use ANGSD to estimate frequencies calculate genotype likelihoods while doing SNP calling and dumping the input files needed for the NgsRelate program | ||
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The first two columns are the individuals number. The next three columns are the estimated relatedness coefficients and the last column is the number of iterations used. | The first two columns are the individuals number. The next three columns are the estimated relatedness coefficients and the last column is the number of iterations used. | ||
= Input file format = | = Input file format = |
Revision as of 22:27, 19 June 2015
Brief description
This page contains information about the program called NgsRelate, which can be used to infer relatedness coefficients for pairs of individuals for low coverage nags data by using genotype likelihoods. To be able to infer the relatedness you will need to know the population frequencies and have genotype likelihoods. This can be done e.g. using the program ANGSD as shown in the example.
Download and Installation
Primary repository is github. https://github.com/ANGSD/NgsRelate
curl https://raw.githubusercontent.com/ANGSD/NgsRelate/master/NgsRelate.cpp >NgsRelate.cpp g++ NgsRelate.cpp -O3 -lz -o NgsRelate
Run example using only ngs data
Assume we have file containing paths to 100 BAM/CRAM files, then we can use ANGSD to estimate frequencies calculate genotype likelihoods while doing SNP calling and dumping the input files needed for the NgsRelate program
./angsd -b filelist -gl 1 -domajorminor 1 -snp_pval 1e-6 - domaf 1 -minmaf 0.05 -doGlf 3 #this generates an angsdput.mafs.gz and a angsdput.glf.gz. #we will need to extract the frequency column from the mafs file and remove the header cut -f5 angsdput.mafs.gz |sed 1d >freq ./ngsrelate -g angsdput.glf.gz -n 100 -f freq -a 0 -b 1 >gl.res
Here we specify that our binary genotype likelihood file contains 100 samples, and that we want to run the analysis for the first two samples -a 0 -b 1. If no -a and -b are specified it will loop through all pairs
Output file format
Example of output
Pair k0 k1 k2 loglh nIter coverage (0,1) 0.673213 0.326774 0.000013 -1710940.769941 19 0.814658
The first two columns are the individuals number. The next three columns are the estimated relatedness coefficients and the last column is the number of iterations used.
Input file format
The input files are binary gz compressed, log like ratios encoded as double. 3 values per sample. The freq file is allowed to be gz compressed.
Citing and references
Changelog
See github for log